Journal cover Journal topic
Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union

Journal metrics

  • IF value: 3.089 IF 3.089
  • IF 5-year<br/> value: 3.700 IF 5-year
  • CiteScore<br/> value: 3.59 CiteScore
  • SNIP value: 1.273 SNIP 1.273
  • SJR value: 2.026 SJR 2.026
  • IPP value: 3.082 IPP 3.082
  • h5-index value: 45 h5-index 45
Atmos. Meas. Tech., 10, 315-332, 2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Research article
27 Jan 2017
Tropospheric temperature measurements with the pure rotational Raman lidar technique using nonlinear calibration functions
Vladimir V. Zuev1,2,3, Vladislav V. Gerasimov1,2, Vladimir L. Pravdin1, Aleksei V. Pavlinskiy1, and Daria P. Nakhtigalova1 1Institute of Monitoring of Climatic and Ecological Systems SB RAS, Tomsk, 634055, Russia
2Tomsk State University, Tomsk, 634050, Russia
3Tomsk Polytechnic University, Tomsk, 634050, Russia
Abstract. Among lidar techniques, the pure rotational Raman (PRR) technique is the best suited for tropospheric and lower stratospheric temperature measurements. Calibration functions are required for the PRR technique to retrieve temperature profiles from lidar remote sensing data. Both temperature retrieval accuracy and number of calibration coefficients depend on the selected function. The commonly used calibration function (linear in reciprocal temperature 1∕T with two calibration coefficients) ignores all types of broadening of individual PRR lines of atmospheric N2 and O2 molecules. However, the collisional (pressure) broadening dominates over other types of broadening of PRR lines in the troposphere and can differently affect the accuracy of tropospheric temperature measurements depending on the PRR lidar system. We recently derived the calibration function in the general analytical form that takes into account the collisional broadening of all N2 and O2 PRR lines (Gerasimov and Zuev, 2016). This general calibration function represents an infinite series and, therefore, cannot be directly used in the temperature retrieval algorithm. For this reason, its four simplest special cases (calibration functions nonlinear in 1∕T with three calibration coefficients), two of which have not been suggested before, were considered and analyzed. All the special cases take the collisional PRR lines broadening into account in varying degrees and the best function among them was determined via simulation. In this paper, we use the special cases to retrieve tropospheric temperature from real PRR lidar data. The calibration function best suited for tropospheric temperature retrievals is determined from the comparative analysis of temperature uncertainties yielded by using these functions. The absolute and relative statistical uncertainties of temperature retrieval are given in an analytical form assuming Poisson statistics of photon counting. The vertical tropospheric temperature profiles, retrieved from nighttime lidar measurements in Tomsk (56.48° N, 85.05° E; Western Siberia, Russia) on 2 October 2014 and 1 April 2015, are presented as an example of the calibration functions application. The measurements were performed using a PRR lidar designed in the Institute of Monitoring of Climatic and Ecological Systems of the Siberian Branch of the Russian Academy of Sciences for tropospheric temperature measurements.

Citation: Zuev, V. V., Gerasimov, V. V., Pravdin, V. L., Pavlinskiy, A. V., and Nakhtigalova, D. P.: Tropospheric temperature measurements with the pure rotational Raman lidar technique using nonlinear calibration functions, Atmos. Meas. Tech., 10, 315-332,, 2017.
Publications Copernicus